aspg-3-3679-1791417349 20261007235549 American Scientific Publishing Group admin@americaspg.com American Scientific Publishing Group Fusion: Practice and Applications FPA 2770-0070 2692-4048 2025 19 2 Sachin Subhashrao Patil Research Scholar, Department of CSE, G H Raisoni University, Amravati (MS), India Sonali Ridhorkar Associate Professor, Department of CSE, G H Raisoni University, Amravati (MS), India Predicting rainfall proves critical for businesses to organize their water resources, make agricultural choices, and prevent disasters. Therefore, proposed model presents a novel approach, namely Heuristic Intelligence towards Enhancing Rainfall Prediction with Artificial Neural Networks (HI2NN) to enhance rainfall prediction by designing heuristic Intelligence combined with Improved Artificial Neural Networks (IANNs). The proposed HI2NN framework leverages heuristic optimization techniques to fine-tune ANN parameters to improve prediction accuracy. Prediction accuracy is computed through our designed custom accuracy metric. The methodology uses historical weather information to extract complex non-linear patterns, which neural models generate from the designed big dataset. The accuracy level of rainfall predictions using our methodology achieves 92%, which demonstrates superior performance than traditional approaches that include random forest and decision tree and XGBoost models. The new forecasting systems develop higher reliability through collaborative efforts between heuristic algorithms and neural networks as described in this research work targeting challenging meteorological forecasts. 2025 288 303 3679 https://creativecommons.org/licenses/by/4.0/ 10.54216/FPA.190221 https://www.americaspg.com/journal/3/article/3679 https://www.americaspg.com/storage/51742379353.pdf